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Sparse pixel vectorization: an algorithm and its performance evaluation

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2 Author(s)
D. Dori ; Fac. of Ind. Eng. & Manage., Technion-Israel Inst. of Technol., Haifa, Israel ; Wenyin Liu

Accurate and efficient vectorization of line drawings is essential for their higher level processing. We present a thinningless sparse pixel vectorization (SPV) algorithm. Rather than visiting all the points along the wire's black area, SPV sparsely visits selected medial axis points. The result is a crude polyline, which is refined through polygonal approximation by removing redundant points. Due to the sparseness of pixel examination and the use of a specialized data structure, SPV is both time efficient and accurate, as evaluated by our proposed performance evaluation criteria

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IEEE Transactions on Pattern Analysis and Machine Intelligence  (Volume:21 ,  Issue: 3 )